School of Engineering
Showing 361-370 of 694 Results
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Craig Levin
Professor of Radiology (Molecular Imaging Program at Stanford/Nuclear Medicine) and, by courtesy, of Physics, of Electrical Engineering and of Bioengineering
Current Research and Scholarly InterestsMolecular Imaging Instrumentation
Laboratory
Our research interests involve the development of novel instrumentation and software algorithms for in vivo imaging of cellular and molecular signatures of disease in humans and small laboratory animal subjects. -
Philip Levis
Professor of Computer Science and of Electrical Engineering
BioProfessor Levis' research focuses on the design and implementation of efficient software systems for embedded wireless sensor networks; embedded network sensor architecture and design; systems programming and software engineering.
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Raymond Levitt
Kumagai Professor in the School of Engineering, Emeritus
Current Research and Scholarly InterestsDr. Levitt founded and directs Stanford’s Global Projects Center (GPC), which conducts research, education and outreach to enhance financing, governance and sustainability of global building and infrastructure projects. Dr. Levitt's research focuses on developing enhanced governance of infrastructure projects procured via Public-Private Partnerships (PPP) delivery, and alternative project delivery approaches for complex buildings like full-service hospitals or data centers.
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Marc Levoy
VMware Founders Professor in Computer Science and Professor of Electrical Engineering, Emeritus
BioLevoy's current interests include the science and art of photography, computational photography, light field sensing and display, and applications of computer graphics in microscopy and biology.
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Adrian Lew
Professor of Mechanical Engineering
BioProf. Lew's interests lie in the broad area of computational solid mechanics. He is concerned with the fundamental design and mathematical analysis of material models and numerical algorithms.
Currently the group is focused on the design of algorithms to simulate hydraulic fracturing. To this end we work on algorithms for time-integration embedded or immersed boundary methods. -
Fei-Fei Li
Sequoia Capital Professor, Senior Fellow at HAI and Professor, by courtesy, of Operations, Information and Technology at the Graduate School of Business
Current Research and Scholarly InterestsAI, Machine Learning, Computer Vision, Robotics, AI+Healthcare, Human Vision
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Percy Liang
Professor of Computer Science and Senior Fellow at the Stanford Institute for Human-Centered AI
BioPercy Liang is an Associate Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011) and the director of the Center for Research on Foundation Models (CRFM). He is currently focused on making foundation models (in particular, language models) more accessible through open-source and understandable through rigorous benchmarking. In the past, he has worked on many topics centered on machine learning and natural language processing, including robustness, interpretability, human interaction, learning theory, grounding, semantics, and reasoning. He is also a strong proponent of reproducibility through the creation of CodaLab Worksheets. His awards include the Presidential Early Career Award for Scientists and Engineers (2019), IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), a Microsoft Research Faculty Fellowship (2014), and paper awards at ACL, EMNLP, ICML, COLT, ISMIR, CHI, UIST, and RSS.
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Michael Lin
Professor of Neurobiology, of Bioengineering and, by courtesy, of Chemical and Systems Biology
Current Research and Scholarly InterestsMy interests are in novel technologies to investigate in vivo biology and improve molecular medicines. These include the use of viral proteases and protease inhibitors to control protein function in vivo, the invention of cofactor-independent photoswitchable proteins for investigating signaling dynamics and controlling gene editing in vivo, the development of fully genetically encoded voltage indicators, and a new approach of treating cancer by rewiring oncogenic pathways to cell ablation.
